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High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
Published on: July 29, 2011
[Assessment of atrial fibrillation inducibility based on epicardial mapping signals]
1Department of Electronic Engineering, Fudan University, Shanghai 200433, P.R.China.
Insights
Early prediction of atrial fibrillation (AF) is crucial. This study developed a method using electrophysiology during sinus rhythm to assess AF vulnerability, achieving high accuracy for early intervention.
Area of Science:
- Cardiology
- Electrophysiology
Background:
- Atrial fibrillation (AF) is a common arrhythmia with serious health consequences.
- Early prediction and intervention are key to managing AF progression.
- Current methods for assessing AF vulnerability require improvement.
Purpose of the Study:
- To develop and validate a novel method for assessing atrial fibrillation (AF) vulnerability.
- To analyze atrial electrophysiology during sinus rhythm to predict AF inducibility.
- To provide a tool for early detection and intervention of AF.
Main Methods:
- Controlled acetylcholine dosage in mongrel dogs to alter AF vulnerability.
- Analysis of atrial epicardial electrophysiology during sinus rhythm.
- Evaluation of atrial activation rhythm variability, earliest activation, delay, and interatrial dyssynchrony.
- Application of binary logistic regression to derive an AF inducibility index.
Main Results:
- The proposed method successfully assessed AF vulnerability in experimental models.
- Classification of sinus rhythm signals based on AF inducibility demonstrated high performance.
- Sensitivity, specificity, and accuracy reached 85.7%, 95.8%, and 91.7%, respectively.
Conclusions:
- The developed electrophysiological analysis method can effectively assess atrial fibrillation (AF) vulnerability.
- This approach holds significant clinical potential for the early prediction and intervention of AF.
- The findings support the use of electrophysiological parameters during sinus rhythm for AF risk stratification.
Abstract:
Atrial fibrillation (AF) is the most common arrhythmia in clinic, which can cause hemodynamic changes, heart failure and stroke, and seriously affect human life and health. As a self-promoting disease, the treatment of AF can become more and more difficult with the deterioration of the disease, and the early prediction and intervention of AF is the key to curbing the deterioration of the disease. Based on this, in this study, by controlling the dose of acetylcholine, we changed the AF vulnerability of five mongrel dogs and tried to assess it by analyzing the electrophysiology of atrial epicardium under different states of sinus rhythm. Here, indices from four aspects were proposed to study the atrial activation rule. They are the variability of atrial activation rhythm, the change of the earliest atrial activation, the change of atrial activation delay and the left-right atrial dyssynchrony. By using binary logistic regression analysis, multiple indices above were transformed into the AF inducibility, which were used to classify the signals during sinus rhythm. The sensitivity, specificity and accuracy of classification reached 85.7%, 95.8% and 91.7%, respectively. As the experimental results show, the proposed method has the ability to assess the AF vulnerability of atrium, which is of great clinical significance for the early prediction and intervention of AF.
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